Archive | Reliability

73

4:28 pm
September 16, 2016
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Quick Return-on-Investment for IIoT Pilot Projects

This slide depicts the infrastructure needed for one of the case studies.(Source: Mitsubishi Electric)

This slide depicts the infrastructure needed for one of the case studies.(Source: Mitsubishi Electric)

As I’m putting together the upcoming Industrial Internet of Things column for October, it’s hard to deny the return-on-investment (ROI) numbers being released at industry conferences and user conferences. At a recent ARC Advisory conference in India, three new applications — from Mitsubishi and Schaeffler — demonstrated the robust ROI for three different industry examples: Continuous Process, hybrid and a discrete production line.

Here’s a quick rundown of these projects and below is a link to the presentation at ARC in India:

These applications include a sensing system, a device and entire production line being connected to a cloud-based system. The waste water case study presented details the return on investment (ROI) and overall costs for a new condition monitoring systems for gearboxes on a line of pumps at this Germany utility.

The results are staggering. Four months after installation of the CMS, the company identified a €3,300 savings for gearwheel defects that were detected. Also, the process avoided a gearbox overhaul and loss of service.

In the paper mill CMS application, the Mitsubishi HiTec Paper wanted to add 26 smartcheck vibration sensors to better monitor a cooling system for its four-story coated thermo-sensitive paper system. After installing the vibration sensor at cost of €25,500, the paper manufacturer reported a €10,500 ROI due to the avoidance of three failures, service-loss and machine damage.

>> Download the Mitsubishi Electric & Schaeffler Group Presentation 

1601Iot_logo>> For more IIoT coverage in maintenance and operations, click here! 

74

1:53 pm
September 14, 2016
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Uptime: When Best Practices Aren’t Enough

By Bob Williamson, Contributing Editor

bobmugnewConsider the following remarks.

“Recently, our top executives announced that our cost of manufacturing still wasn’t what it needed to be, even with all the maintenance improvements and lean initiatives over the past few years. And while our quality and delivery continue to be topnotch, one of our largest customers served an ultimatum that they would be taking their business overseas unless we could improve our pricing.”

“Despite all the maintenance best practices we’ve deployed, we (and others) are finding the department under the cost-cutting knife again. We’ve improved our spare-parts management significantly in the past two years, including stock outs, inventory levels, critical spares, and obsolete parts. Our maintenance labor hours are 90% proactive. But, new equipment continues to be added to the mix to reduce operating labor costs. What should we do?”

Sound familiar?

The real goal

Cost cutting is not a goal. It’s an action deployed as a way to achieve a short-term business goal—one that’s often short lived.

Here’s the challenge: While executives may be preparing for another round of cost cutting, there could be a more powerful alternative. It’s going to take thinking outside the maintenance box, however, to look at manufacturing process reliability. The real goal here is to show management how it can reduce manufacturing costs and position the business for higher earnings growth by tapping into the plant’s hidden capacity.

I recently discussed this approach with a company’s top executives and plant-leadership team. They talked about how strong their business was this year and on into early next year. Their honest concerns centered around getting costs under control to improve the company’s earnings in light of the potential loss of a large customer looking for price cuts. They summarized their strategic performance indicators as three overarching goals:

  • On time, in full—orders shipped to customers on time in the quantity and quality requested.
  • Lead time—reduced time between order received and order shipped.
  • Cost per unit produced—lowest all-in, total cost of making a product.

These executives were describing their goals for a reliable manufacturing process, i.e., a process that performs as intended. Their vision reflects a real opportunity for the organization—one that eclipses another cost-cutting initiative.

Tapping into a plant’s hidden capacity can help cut manufacturing costs and position the business for higher earnings.

Tapping into a plant’s hidden capacity can help cut manufacturing costs and position the business for higher earnings.

Thinking beyond maintenance

Let’s explore this opportunity by thinking about reliable manufacturing processes, i.e., thinking beyond maintenance. The executives who spoke with me agreed to form an improvement team of hand-picked personnel, including the maintenance manager, production operator, maintenance mechanic/union president, front-line supervisor, manufacturing vice president, and the continuous-improvement/quality director. The team used the following data-mining process to get started:

  • Identify the strategic key performance indicators (KPIs), i.e., lagging indicators.
  • Mine company data to determine the leading indicators and what form they take.
  • Determine how plant performance is inhibited, according to the current data.
  • The next step involved a review of top-level indicators that plant leadership was focused on improving, including:
  • labor efficiency variance as a percentage of standard
  • indirect factory labor as a percentage of revenue
  • operating expense as a percentage of revenue
  • obsolete materials and work in process (WIP).

Team members then began to look for specific factors that contributed to labor, operating expense, and materials cost. They also looked for factors that could interrupt flow through the entire manufacturing process to the paying customer.

Based on the team’s review of various ad hoc reports from the company, the improvement team found the most frequently listed reasons for the plant performance losses to be:

  • ran out of work in process (WIP) to meet an order.
  • ran out of raw materials to produce to plan.
  • inaccurate inventory: WIP and raw materials.
  • schedule change: materials delayed upstream.

The improvement team also learned that material cost was the highest cost of manufacturing and labor cost was the lowest.

Asking ‘why’

Drilling down another level into the most-frequently listed reasons for plant-performance losses was the improvement team’s next step: For example, answers to Why did we run out of WIP to meet an order? included:

  • no reason
  • system quantity was different than what actually existed
  • some named items were defective and could not be used.
  • items needed were on quality control hold.

Asking Why did we run out of raw materials to produce to plan at the upstream production processes? revealed some similarities:

  • not enough materials on skid, wrong count.
  • some materials were defective, damaged.

Team members soon recognized that they were discovering why production flow was being interrupted in the plant. In turn, they began wondering if equipment issues, i.e., breakdowns, might also be leading to performance losses. Digging into machine-downtime-tracking information, they found documentation that stated: Machine down for repairs, no operator, no reason listed.

To learn more about the nature of repairs in the plant’s critical-constraint production department, members of the improvement team began discussing machine downtime issues with personnel in the maintenance and operations groups. It was learned that the losses were not so much about equipment breakdowns, but rather:

  • setup problems
  • equipment damage
  • adjustments.

By asking why, the improvement team discovered that machine problems interrupted flow and were possibly linked to inventory and quality issues that had a direct effect on plant performance and the top KPIs (key performance indicators). Unfortunately, other than through maintenance requests, very few machine-related losses were being reported, tracked, or systematically analyzed. This situation had to change if plant reliability was to improve.

Tracking major equipment losses

What equipment-related losses should be tracked to improve plant reliability? The improvement team identified the types of losses that would most likely have a strategic impact on the business: equipment-utilization losses. Here’s how team members agreed to formally collect and categorize equipment performance data for the 17 most critical assets in the plant:

  • Equipment capacity (designed or historical best)
  • Planned capacity losses:
    • Planned shutdown: not scheduled/no demand
    • Planned shutdown: maintenance
    • Planned downtime: not scheduled (breaks, shift change)
  • Planned utilization: time that machine was scheduled to produce something
    • Utilization losses (during scheduled operating time, i.e., the hidden factory):
      • planned downtime: setup/changeover
      • unplanned downtime: no or defective WIP/material
      • unplanned downtime: breakdown
      • unplanned downtime: no operator
      • unplanned downtime: production schedule change and/or interruption
      • efficiency loss: slow-speed or throughput rate
      • efficiency loss: minor stops/startup/adjustment.
    • Yield loss: defects/damaged/scrap output
    • Yield loss: defects/rework
    • Yield loss: startup/adjustment.
  • Actual asset utilization: the bottom line; what the equipment actually delivers).

The reliability mindset

In this case, the improvement team recognized that improving plant reliability is not as much about maintenance as it is about identifying and eliminating equipment-performance losses and interruptions to flow. And, to do that, it’s crucial to have equipment performance data that are accurate and timely.

The good news so far is that top-level executives and other plant leaders have agreed to identify and address the most significant equipment-utilization losses in the manufacturing-flow constraints. Stay tuned for more as this story unfolds. MT

Bob Williamson, CMRP, CPMM, and a member of the Institute of Asset Management, is in his fourth decade of focusing on the people side of world-class maintenance and reliability in plants and facilities across North America. Contact him at RobertMW2@cs.com.

48

2:42 pm
September 13, 2016
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Life-Cycle Costing: Why So Difficult?

0916klausBy Dr. Klaus M. Blache, Univ. of Tennessee, Reliability & Maintainability Center

Life-cycle cost (LCC) represents the total cost of ownership over the complete life of an asset. Calculating LCC, a relatively simple exercise, can lead to better asset-management decisions. This approach has been referred to as cradle-to-grave or inception-to-disposal costing.

Using the stages in the accompanying chart as a guide, vendors/suppliers should be following detailed specifications from purchasing departments to ensure R&M (reliability and maintenance) requirements are met. This graphic is based on the Society of Automotive Engineers (SAE) 1993 & 1999 (document M-110 and 110.2), Reliability and Maintainability Guideline for Manufacturing Machinery and Equipment. (It’s noteworthy that both trades and engineers helped develop this guideline.)

Today there are many computerized LCC models. The concept is simple. Wouldn’t you be willing to pay 10% to 15% more in the initial purchase of machinery and equipment (M&E) if you could save substantially more over the life of those assets?

Overall, operational and maintenance (O&M) costs make up 50% to 80% of total life-cycle costs. By the time the M&E is constructed, however, 95% or more of that cost has already been determined. So, it’s either pay a little more up front or pay much more throughout an asset’s life. The good news is that incorporating “design for maintainability” principles in M&E purchasing decisions can generate substantial O&M cost savings. That means specifications should reflect design-in considerations such as accessibility, modularity, and easy assembly and disassembly. For example, ask:

  • Has the need for accessibility with special tools been considered?
  • To reach a frequently failing component, would items that haven’t failed need to be removed?
  • Would some long-life parts be disposed of with disposable parts?

The objective of LCC is to select the most cost-effective approach, so that the lowest long-term cost of ownership is achieved. Unfortunately, ongoing pressure to save money drives short-term thinking. This was a challenge 30 years ago, and still is today.

screen-shot-2016-09-13-at-9-40-11-am

At a recent Univ. of Tennessee Reliability and Maintainability Center (RMC) meeting in Knoxville, attendees from 50 member companies were polled on LCC matters. Questions and responses included:

Do you have an equation/formula that you use to calculate ROI [return on investment] when making Life-Cycle Asset Management decisions?

  • 76% responded “No.”

How well does your life-cycle process work?

  • Not at all or don’t have one (56%)
  • Not too well (29%)
  • Adequate (10%
  • Very good (5%)
  • Excellent (0%)

How much are design and purchasing (specifications) for R&M needed in buying new equipment?

  • Should always be used (66%)
  • Should be used most of the time (30%)
  • Somewhat needed (4%)
  • Don’t need them (0%)

How much are design and purchasing (specifications) for R&M used in buying new equipment?

  • Somewhat use them (64%)
  • Don’t use them (18%)
  • Regularly use them (9%)
  • Always use them (9%)

These responses indicate a continuing purchasing/manufacturing disconnect. As long as purchasing departments focus mainly on reducing initial costs, this won’t change. Purchasing typically reports to the top of the organization alongside manufacturing, so the battle continues.

What’s needed is a machinery & equipment reliability metric tied to a purchasing department’s performance, not just its cost-saving abilities. After all, LCC decision making is a rich opportunity for organizations. That is if they have the discipline to implement long-term success strategies. MT

Based in Knoxville, Klaus M. Blache is director of the Reliability & Maintainability Center at the Univ. of Tennessee, and a research professor in the College of Engineering. Contact him at kblache@utk.edu.

422

2:43 pm
August 10, 2016
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Heed Drive-Belt Temperature Limits

randmBy Jim Seffrin, Infraspection Institute

Temperature is frequently used to gauge the condition of motors and power-transmission equipment. The following information applies to flexible drive belts and the temperature limits for them.

Drive belts are an integral component on many types of machines. Despite the critical role they play in machine operation, V-type drive belts tend to be out of sight and out of mind until they fail. In most installations, belt temperature largely influences the life of installed V belts.

As a rule of thumb, properly applied and maintained belts should not exceed 140 F (60 C), assuming an ambient temperature of less than 110 F (43 C). Belt life can be greatly reduced by higher operating temperatures. In fact, for every 18 F-deg. (10 C-deg.) increase in belt temperature, belt life is cut in half. Keeping this in mind, we can see that the life of a drive belt operating at 176 F would be reduced by 75%.

Thermogram shows overheating V-belts. Note castoff in the control photo. Images courtesy of Skip Handlin.

Many factors contribute to high belt-operating temperature, including, but not limited to, ambient air temperature, machine design, installation, alignment, and belt tension. Overheating belts that afford line-of-sight access can be readily detected and documented with an infrared imager.

Issues associated with overheating in drive belts may not be limited to the belts themselves, however. With regard to over-tensioned drive belts, excessive force applied to belts is often transferred to bearings in the driven system. In these situations, it’s not uncommon to see bearings overheat due to the excess force created by the over-tensioned belt(s).

Thermogram shows the effects of an improperly tensioned V-belt. In this example, over-tension causes both the belt and adjacent pillow block bearing to run hot.

It should be noted that the operating temperature of overheating drive belts is not necessarily linear. A worn belt that has reached critical temperature will begin to wear at an accelerated rate, which, in turn, will cause the belt to run hotter and wear even more quickly. This vicious cycle will continue until the belt either breaks or fails to perform its intended task.

Once detected, overheating belts should be investigated for cause and proper corrective measures undertaken as soon as possible. Doing so can help prevent unscheduled downtime and may prolong belt life.

Thermal imaging offers several distinct advantages over other types of inspections for belted systems. Thermal imaging is non-contact and nondestructive. Imaging is performed remotely and requires no shutdown of inspected systems. Because infrared imagers produce real-time data, results are instantaneous and allow rapid inspection. MT

Jim Seffrin, a practicing thermographer with 30+ years of experience in the field, was appointed to the position of Director of Infraspection Institute, Burlington, NJ, in 2000. This article is based on one of his “Tip of the Week” posts on IRINFO.org. For more information on infrared applications, as well details on various upcoming training and certification opportunities, email jim@infraspection.com or visit infraspection.com.

28

9:00 am
August 4, 2016
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IIoT Analytics Platform

1608mtprod04pUniformance Suite is a fully integrated system of process software solutions said to turn plant data into actionable information enabling smart operations. The suite uses data analytics to allow users to capture data, visualize trends, collaborate with other users, predict and prevent equipment failures, and act to make informed business decisions. The software collects and stores all types of data for retrieval and analysis, predicts and detects events based on underlying patterns and correlations, links process metrics with business KPIs for decision making, and enables IIoT, mobility, cloud, big data, and predictive and enterprise analytics. Uniformance Insight allows users to visualize process conditions and investigate events from any web browser.
Honeywell Process Solutions
Houston
honeywell.com

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